Deep normative modelling reveals insights into early-stage Alzheimer's disease using multi-modal neuroimaging data
This study highlights the capability of deep normative modelling approaches to detect subtle differences in brain morphology among individuals at risk of developing AD in a non-demented population. Our findings allude to the potential utility of normative deviation metrics in monitoring disease progression.
Authors
- Ana Lawry Aguila (ORCID: https://orcid.org/0000-0003-0727-3274)
- Luigi Lorenzini (ORCID: https://orcid.org/0000-0002-9756-881X)
- Frederik Barkhof (ORCID: https://orcid.org/0000-0003-3543-3706)
- André Altmann (ORCID: https://orcid.org/0000-0002-9265-2393)
- Mohammed Janahi (ORCID: https://orcid.org/0000-0001-7442-2298)
Institutions
- Queen Mary University of London (GB)
- The London College (GB)
- Amsterdam University Medical Centers (NL)
- University College London (GB)
- University of Amsterdam (NL)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
Publication Details
- Journal
- Alzheimer s Research & Therapy
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1186/s13195-025-01753-3
- Citations
- 2
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 2.94
Funders
- Engineering and Physical Sciences Research Council